Many modern companies wish to maintain knowledge in the form of a corporate knowledge
graph and to use and manage this knowledge via a knowledge graph management system …

Graph mining is an important category of graph algorithms that aim to discover structural
patterns such as cliques and motifs in a graph. While a great deal of work has been done …

Over the past decade, distributed dataflow systems (DDS) have become a standard
technology. In these systems, users write programs in restricted dataflow programming …

Adopting a mature AI strategy is fundamental for modern knowledge companies to govern
the proliferation of smart AI-driven applications and to coordinate them within coherent …

There is more than a decade-long history of using static analysis to find bugs in systems
such as Linux. Most of the existing static analyses developed for these systems are simple …

The problem of learning logical rules from examples arises in diverse fields, including
program synthesis, logic programming, and machine learning. Existing approaches either …

Datalog has witnessed promising applications in a variety of domains. We propose a
programming-by-example system, ALPS, to synthesize Datalog programs from input-output …

Datalog has gained prominence in program analysis due to its expressiveness and ease of
use. Its generic fixpoint resolution algorithm over relational domains simplifies the …

The restricted logic programming language Datalog has become a popular implementation
target for deductive-analytic workloads including social-media analytics and program …

Recursive queries have been traditionally studied in the framework of datalog, a language
that restricts recursion to monotone queries over sets, which is guaranteed to converge in …